Crosstalk between the sympathetic nervous system, inflammation and coagulation in gestational diabetes; a therapeutic approach in postmenopausal hypertension

The occurrence of gestational diabetes (GDM) during pregnancy is a powerful sign of a risk of later type 2 diabetes (T2D) and cardiovascular diseases (CVDs). The physiological basis for this disease progression is not yet fully understood, but increasing evidence exists on interplay of insulin resistance, subclinical inflammation, and more recently, on unbalance of the autonomic nervous system. Since the delay in development of T2D and CVD after GDM ranges from years to decades, better understanding of the pathophysiology of GDM could give us new tools for primary prevention. The present study was aimed at investigating the role of the sympathetic nervous system (SNS) in GDM and its associations with insulin and a variety of inflammatory cytokines and coagulation and fibrinolysis markers. This thesis covers two separate study lines. Firstly, we investigated 41 women with GDM and 22 healthy pregnant and 14 non-pregnant controls during the night in hospital. Blood samples were drawn at 24:00, 4:00 and 7:00 h to determine the concentrations of plasma glucose, insulin, noradrenaline (NA) and adrenomedullin, markers of subclinical inflammation, coagulation and fibrinolysis variables and platelet function. Overnight holter ECG recording was performed for analysis of heart rate variability (HRV). Secondly, we studied 87 overweight hypertensive women with natural menopause. They were randomised to use a central sympatholytic agent, moxonidine (0.3mg twice daily), the β-blocking agent atenolol (50 mg once daily+blacebo once daily) for 8 weeks. Inflammatory markers and adiponectin were analysed at the beginning and after 8 weeks. Activation of the SNS (increase in NA, decreased HRV) was seen in pregnant vs. non-pregnant women, but no difference existed between GDM and normal pregnancy. However, modulation (internal rhythm) of HRV was attenuated in GDM. Insulin and inflammatory cytokine levels were comparable in all pregnant women but nocturnal variation of concentrations of C-reactive protein, serum amyloid A and insulin were reduced in GDM. Levels of coagulation factor VIII were lower in GDM compared with normal pregnancy, whereas no other differences were seen in coagulation and fibrinolysis markers. No significant associations were seen between NA and the studied parameters. In the study of postmenopausal women, moxonidine treatment was associated with favourable changes in the inflammatory profile, seen as a decrease in TNFα concentrations (increase in atenolol group) and preservation of adiponectin levels (decrease in atenolol group). In conclusion, our results did not support our hypotheses of increased SNS activity in GDM or a marked association between NA and inflammatory and coagulation markers. Reduced biological variation of HRV, insulin and inflammatory cytokines suggests disturbance of autonomic and hormonal regulatory mechanisms in GDM. This is a novel finding. Further understanding of the regulatory mechanisms could allow earlier detection of risk women and the possibility of prevention. In addition, our results support consideration of the SNS as one of the therapeutic targets in the battle against metabolic diseases, including T2D and CVD.

Media Education in the Finnish School System : A Conceptual Analysis of the Subject Didactic Dimension of Media Education

The aim of the doctoral dissertation was to further our theoretical and empirical understanding of media education as practised in the context of Finnish basic education. The current era of intensive use of the Internet is recognised too. The doctoral dissertation presents the subject didactic dimension of media education as one of the main results of the conceptual analysis. The theoretical foundation is based on the idea of dividing the concept of media education into media and education (Vesterinen et al., 2006). As two ends of the dimension, these two can be understood didactically as content and pedagogy respectively. In the middle, subject didactics is considered to have one form closer to content matter (Subject Didactics I learning about media) and another closer to general pedagogical questions (Subject Didactics II learning with/through media). The empirical case studies of the dissertation are reported with foci on media literacy in the era of Web 2.0 (Kynäslahti et al., 2008), teacher reasoning in media educational situations (Vesterinen, Kynäslahti - Tella, 2010) and the research methodological implications of the use of information and communication technologies in the school (Vesterinen, Toom - Patrikainen, 2010). As a conclusion, Media-Based Media Education and Cross-Curricular Media Education are presented as two subject didactic modes of media education in the school context. Episodic Media Education is discussed as the third mode of media education where less organised teaching, studying and learning related to media takes place, and situations (i.e. episodes, if you like) without proper planning or thorough reflection are in focus. Based on the theoretical and empirical understanding gained in this dissertation, it is proposed that instead of occupying a corner of its own in the school curriculum, media education should lead the wider change in Finnish schools.

Diastereomeric Drug Glucuronides: Enzymatic Glucuronidation and Analysis by Capillary Electrophoresis and Liquid Chromatography-Mass Spectrometry

Foreign compounds, such as drugs are metabolised in the body in numerous reactions. Metabolic reactions are divided into phase I (functionalisation) and phase II (conjugation) reactions. Uridine diphosphoglucuronosyltransferase enzymes (UGTs) are important catalysts of phase II metabolic system. They catalyse the transfer of glucuronic acid to small lipophilic molecules and convert them to hydrophilic and polar glucuronides that are readily excreted from the body. Liver is the main site of drug metabolism. Many drugs are racemic mixtures of two enantiomers. Glucuronidation of a racemic compound yields a pair of diastereomeric glucuronides. Stereoisomers are interesting substrates in glucuronidation studies since some UGTs display stereoselectivity. Diastereomeric glucuronides of O-desmethyltramadol (M1) and entacapone were selected as model compounds in this work. The investigations of the thesis deal with enzymatic glucuronidation and the development of analytical methods for drug metabolites, particularly diastereomeric glucuronides. The glucuronides were analysed from complex biological matrices, such as urine or from in vitro incubation matrices. Various pretreatment techniques were needed to purify, concentrate and isolate the analytes of interest. Analyses were carried out by liquid chromatography (LC) with ultraviolet (UV) or mass spectrometric (MS) detection or with capillary electromigration techniques. Commercial glucuronide standards were not available for the studies. Enzyme-assisted synthesis with rat liver microsomes was therefore used to produce M1 glucuronides as reference compounds. The glucuronides were isolated by LC/UV and ultra performance liquid chromatography (UPLC)/MS, while tandem mass spectrometry (MS/MS) and nuclear magnetic resonance (NMR) spectroscopy were employed in structural characterisation. The glucuronides were identified as phenolic O-glucuronides of M1. To identify the active UGT enzymes in (±)-M1 glucuronidation recombinant human UGTs and human tissue microsomes were incubated with (±)-M1. The study revealed that several UGTs can catalyse (±)-M1 glucuronidation. Glucuronidation in human liver microsomes like in rat liver microsomes is stereoselective. The results of the studies showed that UGT2B7, most probably, is the main UGT responsible for (±)-M1 glucuronidation in human liver. Large variation in stereoselectivity of UGTs toward (±)-M1 enantiomers was observed. Formation of M1 glucuronides was monitored with a fast and selective UPLC/MS method. Capillary electromigration techniques are known for their high resolution power. A method that relied on capillary electrophoresis (CE) with UV detection was developed for the separation of tramadol and its free and glucuronidated metabolites. The suitability of the method to identify tramadol metabolites in an authentic urine samples was tested. Unaltered tramadol and four of its main metabolites were detected in the electropherogram. A micellar electrokinetic chromatography (MEKC) /UV method was developed for the separation of the glucuronides of entacapone in human urine. The validated method was tested in the analysis of urine samples of patients. The glucuronides of entacapone could be quantified after oral entacapone dosing.

Theory and Analysis of Classic Heavy Metal Harmony

This thesis explores melodic and harmonic features of heavy metal, and while doing so, explores various methods of music analysis; their applicability and limitations regarding the study of heavy metal music. The study is built on three general hypotheses according to which 1) acoustic characteristics play a significant role for chord constructing in heavy metal, 2) heavy metal has strong ties and similarities with other Western musical styles, and 3) theories and analytical methods of Western art music may be applied to heavy metal. It seems evident that in heavy metal some chord structures appear far more frequently than others. It is suggested here that the fundamental reason for this is the use of guitar distortion effect. Subsequently, theories as to how and under what principles heavy metal is constructed need to be put under discussion; analytical models regarding the classification of consonance and dissonance and chord categorization are here revised to meet the common practices of this music. It is evident that heavy metal is not an isolated style of music; it is seen here as a cultural fusion of various musical styles. Moreover, it is suggested that the theoretical background to the construction of Western music and its analysis can offer invaluable insights to heavy metal. However, the analytical methods need to be reformed to some extent to meet the characteristics of the music. This reformation includes an accommodation of linear and functional theories that has been found rather rarely in music theory and musicology.

Computational Methods for Reconstruction and Analysis of Genome-Scale Metabolic Networks

Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the analysis of large metabolic models encompassing the whole metabolism of one or several organisms. We concentrate on three major themes of metabolic modeling: metabolic pathway analysis, metabolic reconstruction and the study of evolution of metabolism. In the first part of this thesis, we study metabolic pathway analysis. We propose a novel modeling framework called gapless modeling to study biochemically viable metabolic networks and pathways. In addition, we investigate the utilization of atom-level information on metabolism to improve the quality of pathway analyses. We describe efficient algorithms for discovering both gapless and atom-level metabolic pathways, and conduct experiments with large-scale metabolic networks. The presented gapless approach offers a compromise in terms of complexity and feasibility between the previous graph-theoretic and stoichiometric approaches to metabolic modeling. Gapless pathway analysis shows that microbial metabolic networks are not as robust to random damage as suggested by previous studies. Furthermore the amino acid biosynthesis pathways of the fungal species Trichoderma reesei discovered from atom-level data are shown to closely correspond to those of Saccharomyces cerevisiae. In the second part, we propose computational methods for metabolic reconstruction in the gapless modeling framework. We study the task of reconstructing a metabolic network that does not suffer from connectivity problems. Such problems often limit the usability of reconstructed models, and typically require a significant amount of manual postprocessing. We formulate gapless metabolic reconstruction as an optimization problem and propose an efficient divide-and-conquer strategy to solve it with real-world instances. We also describe computational techniques for solving problems stemming from ambiguities in metabolite naming. These techniques have been implemented in a web-based sofware ReMatch intended for reconstruction of models for 13C metabolic flux analysis. In the third part, we extend our scope from single to multiple metabolic networks and propose an algorithm for inferring gapless metabolic networks of ancestral species from phylogenetic data. Experimenting with 16 fungal species, we show that the method is able to generate results that are easily interpretable and that provide hypotheses about the evolution of metabolism.

Construction of a global map of human gene expression : the process, tools and analysis

This thesis studies human gene expression space using high throughput gene expression data from DNA microarrays. In molecular biology, high throughput techniques allow numerical measurements of expression of tens of thousands of genes simultaneously. In a single study, this data is traditionally obtained from a limited number of sample types with a small number of replicates. For organism-wide analysis, this data has been largely unavailable and the global structure of human transcriptome has remained unknown. This thesis introduces a human transcriptome map of different biological entities and analysis of its general structure. The map is constructed from gene expression data from the two largest public microarray data repositories, GEO and ArrayExpress. The creation of this map contributed to the development of ArrayExpress by identifying and retrofitting the previously unusable and missing data and by improving the access to its data. It also contributed to creation of several new tools for microarray data manipulation and establishment of data exchange between GEO and ArrayExpress. The data integration for the global map required creation of a new large ontology of human cell types, disease states, organism parts and cell lines. The ontology was used in a new text mining and decision tree based method for automatic conversion of human readable free text microarray data annotations into categorised format. The data comparability and minimisation of the systematic measurement errors that are characteristic to each lab- oratory in this large cross-laboratories integrated dataset, was ensured by computation of a range of microarray data quality metrics and exclusion of incomparable data. The structure of a global map of human gene expression was then explored by principal component analysis and hierarchical clustering using heuristics and help from another purpose built sample ontology. A preface and motivation to the construction and analysis of a global map of human gene expression is given by analysis of two microarray datasets of human malignant melanoma. The analysis of these sets incorporate indirect comparison of statistical methods for finding differentially expressed genes and point to the need to study gene expression on a global level.

Categorical Meteorological Products: Evaluation and Analysis

In meteorology, observations and forecasts of a wide range of phenomena for example, snow, clouds, hail, fog, and tornados can be categorical, that is, they can only have discrete values (e.g., "snow" and "no snow"). Concentrating on satellite-based snow and cloud analyses, this thesis explores methods that have been developed for evaluation of categorical products and analyses. Different algorithms for satellite products generate different results; sometimes the differences are subtle, sometimes all too visible. In addition to differences between algorithms, the satellite products are influenced by physical processes and conditions, such as diurnal and seasonal variation in solar radiation, topography, and land use. The analysis of satellite-based snow cover analyses from NOAA, NASA, and EUMETSAT, and snow analyses for numerical weather prediction models from FMI and ECMWF was complicated by the fact that we did not have the true knowledge of snow extent, and we were forced simply to measure the agreement between different products. The Sammon mapping, a multidimensional scaling method, was then used to visualize the differences between different products. The trustworthiness of the results for cloud analyses [EUMETSAT Meteorological Products Extraction Facility cloud mask (MPEF), together with the Nowcasting Satellite Application Facility (SAFNWC) cloud masks provided by Météo-France (SAFNWC/MSG) and the Swedish Meteorological and Hydrological Institute (SAFNWC/PPS)] compared with ceilometers of the Helsinki Testbed was estimated by constructing confidence intervals (CIs). Bootstrapping, a statistical resampling method, was used to construct CIs, especially in the presence of spatial and temporal correlation. The reference data for validation are constantly in short supply. In general, the needs of a particular project drive the requirements for evaluation, for example, for the accuracy and the timeliness of the particular data and methods. In this vein, we discuss tentatively how data provided by general public, e.g., photos shared on the Internet photo-sharing service Flickr, can be used as a new source for validation. Results show that they are of reasonable quality and their use for case studies can be warmly recommended. Last, the use of cluster analysis on meteorological in-situ measurements was explored. The Autoclass algorithm was used to construct compact representations of synoptic conditions of fog at Finnish airports.